Detection and Counting of Fake Currency & Genuine Currency Using Image Processing

Abstract

In today's digital age, the proliferation of counterfeit currency poses a significant challenge to financial institutions and businesses worldwide. The detection and prevention of counterfeit currency transactions require advanced technological solutions to safeguard the integrity of financial systems. In our research, we present a novel approach to tackle this problem by leveraging image processing techniques. The proposed system utilizes state-of-the-art image processing algorithms to distinguish between fake and genuine currency notes accurately. By analyzing various features such as texture, color, and watermark patterns, our system can effectively identify counterfeit currency notes with high precision. Additionally, the system is capable of counting and validating genuine currency notes, providing a comprehensive solution for currency authentication and management. The integration of image processing technology into currency verification systems offers numerous benefits, including enhanced accuracy, speed, and reliability. Our research aims to contribute to the development of robust and efficient solutions for combating counterfeit currency fraud, thereby safeguarding the integrity of financial transactions and promoting trust in monetary systems.